Human Abnormal Behavior Impact on Speaker Verification Systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10239776" target="_blank" >RIV/61989100:27240/18:10239776 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/18:10239776
Result on the web
<a href="https://ieeexplore.ieee.org/document/8409958" target="_blank" >https://ieeexplore.ieee.org/document/8409958</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2018.2854960" target="_blank" >10.1109/ACCESS.2018.2854960</a>
Alternative languages
Result language
angličtina
Original language name
Human Abnormal Behavior Impact on Speaker Verification Systems
Original language description
Human behavior plays a major role in improving human-machine communication. The performance must be affected by abnormal behavior as systems are trained using normal utterances. The abnormal behavior is often associated with a change in the human emotional state. Different emotional states cause physiological changes in the human body that affect the vocal tract. Fear, anger, or even happiness we recognize as a deviation from a normal behavior. The whole spectrum of human-machine application is susceptible to behavioral changes. Abnormal behavior is a major factor, especially for security applications such as verification systems. Face, fingerprint, iris, or speaker verification is a group of the most common approaches to biometric authentication today. This paper discusses human normal and abnormal behavior and its impact on the accuracy and effectiveness of automatic speaker verification (ASV). The support vector machines classifier inputs are Mel-frequency cepstral coefficients and their dynamic changes. For this purpose, the Berlin Database of Emotional Speech was used. Research has shown that abnormal behavior has a major impact on the accuracy of verification, where the equal error rate increase to 37 %. This paper also describes a new design and application of the ASV system that is much more immune to the rejection of a target user with abnormal behavior.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/LM2015070" target="_blank" >LM2015070: IT4Innovations National Supercomputing Center</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Access
ISSN
2169-3536
e-ISSN
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Volume of the periodical
6
Issue of the periodical within the volume
July
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
40120-40127
UT code for WoS article
000441375000001
EID of the result in the Scopus database
2-s2.0-85049804543